After that, all of the processing logic is the same.

But because of our changes in `GzipRequest.body`, the request body will be automatically decompressed when it is loaded by **FastAPI** when needed.

## Accessing the request body in an exception handler { #accessing-the-request-body-in-an-exception-handler }

/// tip

And of course, it supports the same:

* data validation
* data serialization
* data documentation, etc.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

         * processes one artifact at a time and hence cannot associate the artifacts from the same project to use the
         * same version index. Allowing the caller to pass in metadata from a previous deployment allows to re-establish
         * the association between the artifacts of the same project.
         */
        for (Iterator<? extends Metadata> it = metadatas.iterator(); it.hasNext(); ) {

@GwtCompatible
public abstract class DiscreteDomain<C extends Comparable> {

  /**
   * Returns the discrete domain for values of type {@code Integer}.
   *
   * <p>This method always returns the same object. That object is serializable; deserializing it
   * results in the same object too.
   *
   * @since 14.0 (since 10.0 as {@code DiscreteDomains.integers()})
   */
  public static DiscreteDomain<Integer> integers() {
    return IntegerDomain.INSTANCE;

final class Platform {

  private static final char[] CHAR_BUFFER = new char[1024];

  static char[] charBufferFromThreadLocal() {
    // ThreadLocal is not available to GWT, so we always reuse the same
    // instance.  It is always safe to return the same instance because
    // javascript is single-threaded, and only used by blocks that doesn't
    // involve async callbacks.
    return CHAR_BUFFER;
  }

  private Platform() {}

 *
 * This leads to a second side effect in that any @Inject request for just ModelProcessor in
 * the same injector is immediately matched to this explicit binding, which means extensions
 * cannot override this binding. This is because the lookup is always short-circuited in this
 * specific situation (plain @Inject request, and plain explicit binding for the same type.)
 *
 * The simplest solution is to use a custom @Named here so it isn't bound under the plain key.

If you pass a "callable" as a dependency in **FastAPI**, it will analyze the parameters for that "callable", and process them in the same way as the parameters for a *path operation function*. Including sub-dependencies.

That also applies to callables with no parameters at all. The same as it would be for *path operation functions* with no parameters.

 *     their equivalent on the result of {@code Traverser.forTree(tree)} where {@code tree}
 *     implements {@code SuccessorsFunction}, which has a similar API as {@link #children} or can be
 *     the same lambda function as passed into {@link #using(Function)}.
 */
// This class is now only available externally for backwards compatibility; it should not be used

Then you declare your data model as a class that inherits from `BaseModel`.

Use standard Python types for all the attributes:

{* ../../docs_src/body/tutorial001_py310.py hl[5:9] *}


The same as when declaring query parameters, when a model attribute has a default value, it is not required. Otherwise, it is required. Use `None` to make it just optional.

        map sigbuild-r2.12-python3.9 2.12-python3.9
        map sigbuild-r2.12-python3.10 2.12-python3.10
        map sigbuild-r2.12-python3.11 2.12-python3.11
        # TF 2.12 + Clang (containers are the same, but env vars in configs.bzl are different)
        map sigbuild-r2.12-clang 2.12-python3.9
        map sigbuild-r2.12-clang-python3.8 2.12-python3.8
        map sigbuild-r2.12-clang-python3.9 2.12-python3.9